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The IC-WHCD100 (Inspire) is intended to be used as an aid in the detection and diagnosis of dental caries.

The IC-WHCD100 is a toothbrush-sized handpiece used for diagnosis of caries. A USB cable is used to connect the handpiece to a personal computer with a dental imaging software. After a camera cover is placed over the end, the handpiece is positioned over the tooth to be examined. The camera takes images by illuminating the tooth surface with a white LED light for regular tooth image. With fluoresced light, the device can show bacteria on the surface of tooth. With infrared light, the device can show tooth cavity by highlighting enamel. The user can view the images on 510k cleared dental imaging software such as Apteryx vision (K983111), Romexis (K171385), Sidexis (K132773), etc.

The provided text details the FDA 510(k) summary for the IC-WHCD100 (Inspire) device, which is an intraoral camera intended as an aid in the detection and diagnosis of dental caries. However, the document primarily focuses on demonstrating substantial equivalence to predicate devices and provides limited information regarding specific acceptance criteria and detailed study results. Critical information needed to fully answer the request, such as a precise table of acceptance criteria and reported device performance with numerical metrics (e.g., sensitivity, specificity for caries detection), detailed sample size for the test set, number and qualifications of experts for ground truth, adjudication methods, details of comparative effectiveness studies (MRMC), or a comprehensive standalone performance study report are not explicitly present in the provided text.

Based on the available information, here's what can be extracted and what remains unknown:

1. Table of Acceptance Criteria and Reported Device Performance

The document mentions "Performance Test for imaging (Image Sharpness, Image Size, Image Resolution, tooth Caries Detection)" as a non-clinical test. However, it does not provide a specific table of acceptance criteria or the reported device performance metrics (e.g., sensitivity, specificity, accuracy) for caries detection. It only broadly states that "the performance test results of the subject device supports that the transillumination mode works well despite this difference." and "the performance test result supports that the subject device is substantially equivalent to the predicate devices."

Unfortunately, a specific table with numerical acceptance criteria and corresponding performance data for caries detection is not found in the provided text.

2. Sample Size Used for the Test Set and Data Provenance

The document states "performance test results of the subject device supports that the transillumination mode works well despite this difference." and refers to "Performance Tests (Non-clinical)". However, the specific sample size used for the test set (number of teeth, lesions, or patients) and the data provenance (e.g., country of origin of the data, retrospective or prospective nature of data collection) are not disclosed in this 510(k) summary.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The provided text does not specify the number of experts used to establish ground truth or their qualifications. It only refers to "Performance Tests" related to caries detection, implying some form of ground truth was used, but details are absent.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) used for establishing the ground truth for the test set.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done

The provided text does not mention or describe a Multi Reader Multi Case (MRMC) comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The focus is on the device's performance relative to predicate devices, not human-AI collaboration.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done

The document broadly states "Performance Test for imaging... tooth Caries Detection)". While the device has a caries detection aid capability, the summary does not explicitly detail a standalone algorithm-only performance study with specific metrics (e.g., sensitivity, specificity of the algorithm itself). The device is described as an "aid in the detection and diagnosis," implying human involvement.

7. The Type of Ground Truth Used

The document refers to "tooth Caries Detection" as one of the performance tests. However, the specific type of ground truth used (e.g., expert consensus, pathology/histology, clinical outcomes data, or a combination) is not explicitly stated.

8. The Sample Size for the Training Set

The 510(k) summary does not provide any information regarding a training set sample size. This type of document typically focuses on performance testing for regulatory clearance rather than details of model development. Given that the device is an "intraoral camera with Caries Detection Aid" using specific light sources (405nm and 940nm) to highlight bacteria and cavities, it's possible its "detection aid" might be based on optical properties rather than a complex AI model requiring extensive training data in the traditional sense, but this is speculative given the lack of detail.

9. How the Ground Truth for the Training Set Was Established

Since there is no mention of a training set, there is no information on how its ground truth was established.

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Dr's Light 2 is a hand held LED polymerization light intended to cure dental composites using visible light.

Not Found

This document, K173157, is a 510(k) premarket notification for a dental device called "Dr.'s Light 2." It is a regulatory approval letter from the FDA. Based on the provided text, there is no information about acceptance criteria for a study, performance metrics, sample sizes, expert qualifications, or any details related to an AI/algorithm-based medical device study.

The document states that the device is a "hand held LED polymerization light intended to cure dental composites using visible light." This is a physical, light-emitting device, not a software or AI-driven diagnostic or analytical tool that would typically involve the kind of studies you are asking about (e.g., MRMC, standalone algorithm performance, ground truth establishment through expert consensus or pathology).

Therefore, I cannot fulfill your request to describe acceptance criteria and a study proving the device meets them, as the provided input does not contain any of that information. The document is solely an FDA clearance letter for a non-AI dental light.

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Dr's Finder NEO is intended for detecting the apex of root canal.

The device allows the relative position of a dental file and the apex to be determined electrically. Using a standard dental file inserted into the root canal as an electrode, the device emits very small electrical currents having frequencies of 400 Hz, and 10400 Hz. The current between the file and mouth is measured at each of these frequencies, and the readout of the relative proximity to the apex will appear on the meter.

The provided text describes the Dr's Finder NEO, an apex locator device, and its substantial equivalence to predicate devices. Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The document mentions "comparison testing on Dr's Finder NEO and the predicate device (RCM-7, K090925) was performed to compare the measurement performance of locating apex root using extracted tooth and a stainless steel file."

• Test Set Sample Size: Not explicitly stated. The phrase "extracted tooth" implies multiple teeth were used, but a specific number is not provided.
• Data Provenance: The study used "extracted tooth," suggesting an in vitro setting. The country of origin for the data is not specified, but the manufacturer is Good Doctors Co., Ltd. from the Republic of Korea. The study appears to be prospective in nature as it was conducted for this 510(k) submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The ground truth method described below does not inherently require human expert interpretation as the measurement is electrical.

4. Adjudication Method for the Test Set

Not applicable. The "ground truth" for an apex locator's accuracy is typically established by direct measurement relative to the actual apical foramen in an ex vivo setting, rather than through expert adjudication of images or clinical findings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the Effect Size of Human Improvement

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The study conducted was a technical performance comparison between two devices, not an evaluation of human reader performance with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was Done

Yes, a standalone performance test was done. The document states, "The comparison testing on Dr's Finder NEO and the predicate device (RCM-7, K090925) was performed to compare the measurement performance of locating apex root using extracted tooth and a stainless steel file." This describes the device operating on its own to locate the apex.

7. The Type of Ground Truth Used

The ground truth explicitly stated for accuracy is ±0.2mm. For an apex locator, this ground truth is typically established by:

• Direct Measurement/Physical Measurement: In an ex vivo setting (e.g., extracted teeth), the actual length to the anatomical apex is physically measured (e.g., with a microscope or calipers after sectioning) and compared to the device's reading. The document's mention of "extracted tooth" supports this type of ground truth.

8. The Sample Size for the Training Set

The document does not mention a training set. Apex locators like the Dr's Finder NEO are typically based on electrical impedance principles and calibrated during manufacturing, rather than "trained" in the machine learning sense with a data set.

9. How the Ground Truth for the Training Set Was Established

As no training set is discussed or implied by the technology, this question is not applicable based on the provided information.

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